Design of Risk Management Strategies in Business Process Information Flow

1
Design of Risk Management Strategies in Business
Process Information Flow

• Xue Bai
• Operations and Information Management
• School of Business
• University of Connecticut

2
Outline

• Motivation and problem definition
• Methodology
• Experimental study
• Real world application
• Future research

3
Motivation

• Impact of errors in corporate business processes
• 10 percent to 30 percent of the data flowing
  through corporate systems is bad (CFO magazine
  2003)
• Impact of errors in healthcare processes
• More than 8.8 million ADEs occur each year in
  ambulatory care, cost at least 5,000 per ADE.
  Medication errors account for 1 out of 131
  ambulatory care deaths (Washington eHealth
  Initiative 2004).
• Health care data quality accuracy 67,
  completeness 30.7 (Stein et al. 2000)
• Legal mandates
• Sarbanes Oxley Act (2002)
• HIPAA (1996), Medical malpractice laws

4
An Example of BP with Errors and Risks
An example a medication process
Call back and complain
Wrong dosage
Medication
Pharmacist
Prescription
Call back and complain
Formulary mismatch
Prescription
Adverse Drug Event
Physician
Patient
Bill
Call back and complain
Bill
Insurer
Call back efforts ? Administrative cost
? Patient satisfaction loyalty litigation
issues. ?
Patient ends up in ER. ?
Manual check
E-prescribing systems
Performance review
E-order systems
Bills for ER visit. ?
5
An Example of BP with Errors and Risks
A medication process
Medication
Pharmacy
Prescription
Prescription
Physician
Patient
Bill
Bill
Insurer
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Elements of the Model

• A Business Process (BP)
• Tasks
• Information flow
• Errors
• Accuracy
• Completeness
• Occurrence
• Risk exposure
• Design of Control structure
• for risk management

check alert info.
database
enter order info.
enter order info.
order
update medication info.
The order management process at the pharmacy
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Outline

• Motivation and problem definition
• Methodology
• Experimental study
• Real world application
• Future research

8
Process Structure Affects Error Impact
A Simple Sequential Process
Update medication information
Update medication information
Database
Database
Enter order information
Check alert info.
Check alert info.
Enter order information

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Process Structure Affects Control Function
A Simple Parallel Process
Order of medication
Preparing voucher package
Shipping invoice
Payment voucher
10
BP as a Graph
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BP as a Graph
The volume transition matrixp(T) the ratio
between the volume output by task i and the
volume fed to task j, given tij 1.
12
Impact of Error

• The propagation impact (PI) matrix
• K the length of the longest path in a process.
• p(T) the volume transition matrix
• The propagation potential

13
Error Generation

• Error correlation structure
• Models for error generation processes
  hierarchical sampling schema
• Controlling for dependence/independence due to
  the homogeneity/ heterogeneity of operations and
  resources involved
• Within a task
• Across tasks

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Error Propagation

• The number of errors of type m at task i
• number of errors of type m that show up at
  task i
• number of errors of type m that arrive at
  task i
• occurrence of errors of type m generated
  by task i
• average number of eim

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Loss and Risk Measurement

• Loss
• cim cost of an error of type m at task i.
• Risk Measures
• Expected Loss (EL), Value-at-Risk (VaR),
  Conditional Value-at-Risk (CVaR)

EL
CVaR
VaR
ß
loss
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Risk Measures

• Expected Loss
• Value-at-Risk
• Conditional Value-at-Risk

17
Risk Management Control Model

• Control allocation factor
• Effectiveness of control
• the probability of a control catching an error
• Deterministic control
• Stochastic control
• Cost of control (per period)

18
Model Formulation I, II, and III

• Design problem Given a budget B,
• Model I Expected-Loss-Optimal Control
  Structure
• Model II ß-VaR-Optimal Control Structure
• Model III ß-CVaR-Optimal Control Structure

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Outline

• Motivation and problem definition
• Methodology
• Experimental study
• Real world application
• Future research

20
Experimental Study

• Experimental design
• Topological variation
• Sequential, parallel, arbitrary
• Process size
• Small (4 tasks), medium (10 tasks), large (25
  tasks)
• Cost of control vs. Loss per error ( )
• Expensive (500, 1000, 2000, 4000, 10000),
  inexpensive (25, 50, 100)
• Tolerance level of risks (ß)
• ß 0.90, 0.95, 0.99
• Error correlation
• Independent, dependent

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Experimental Results

• As the process size increases, (Table 113, 115,
  117, 119, 121, and 123)
• The optimal amount of control allocation in total
  increases
• The optimal amount of control allocation at each
  task decreases
• For sequential structure, the objective function
  value increases exponentially for parallel
  structure, the magnitude remains the same.
• As the tolerance level of risks (ß) changes
  (Table 2 and 10 Table 22 and 30),
• The optimal amount of control allocation in total
  increases
• The impact of ß at the task level depends on
  characteristics of the loss distributions
• In the range of ß value and loss distributions
  tested, the impact is insignificant.
• As the ratio cost of control / loss per error (
  ) increases (Table 153-159)
• The optimal amount of control allocation at each
  task decreases
• The optimal amount of control allocation in total
  decreases

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Experimental Results (continue)

• Optimal control allocations depend on risk
  objectives.
• The relative importance of each task location
  changes accordingly
• Tradeoffs when consider multi-risk objectives
• For processes with sequential structure, holding
  other factors constant,
• The highest control allocations occur at tasks
  towards the center of the process.
• For processes with parallel structure, holding
  other factors constant,
• The highest control allocations occur at the
  merging tasks of the process.

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Outline

• Motivation and problem definition
• Methodology
• Experimental study
• Real world application
• Future research

24
Case Study

• An Order Fulfillment Process
• The Data 15 tasks, 13 internal tasks, 46
  errors that occur in different tasks, costs per
  error per type, frequencies of error occurrences,
  cost factors of controls, based 1200 orders per
  month.

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Results Optimal Allocation of Control Resource
The tasks 0) Clients place order, 1) Enter
order information, 2) Check payer and insurance
info. 3) Create/update contracts, 4) Prove
prescription, 5) Prepare prescribed items, 6)
Dispense from alternative source, 7) Submit drug
orders to wholesaler, 8) Deliver medication, 9)
Prepare and send claims to an insurance company
or 10) to the responsible party, 11) Collect
payments, 12) Post payments and prepare vouchers,
13) Update ledgers, 14) insurer/clients pay bills.
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Results Optimal Objective Function Values
The tasks 0) Clients place order, 1) Enter
order information, 2) Check payer and insurance
info. 3) Create/update contracts, 4) Prove
prescription, 5) Prepare prescribed items, 6)
Dispense from alternative source, 7) Submit drug
orders to wholesaler, 8) Deliver medication, 9)
Prepare and send claims to an insurance company
or 10) to the responsible party, 11) Collect
payments, 12) Post payments and prepare vouchers,
13) Update ledgers, 14) insurer/clients pay bills.
27
Outline

• Motivation and problem definition
• Methodology
• Experimental study
• Real world application
• Future research

28
Future research

• Summary
• Risk management models for error associated risks
  in business process information flow
• Future research
• Sensitivity analysis of the effect of other
  factors on optimal control allocations and risk
  objectives
• Loss per error, Control effectiveness, Cost
  structure of controls, Topological redesign,
  Analytic solution for CVaR
• Managerial problems
• Multi-Objective Optimization
• Find the maximum confidence level ß for a given
  value-at-risk
• Given the output errors, identify the most
  probable error sources
• Many others.